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Research Of Face Recognition Algorithm Based On Gabor Filter And Manifold Learning Theory

Posted on:2015-06-07Degree:MasterType:Thesis
Country:ChinaCandidate:Y ShiFull Text:PDF
GTID:2298330452950658Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
In this paper,the face recognition as the goal,in order to improve performance androbustness of face recognition.The main research of face recognition algorithmbased on Gabor filter and the theory of manifold learning.The main work done is asfollows:(1)This paper reviews the research status and significance of face recognitiontechnology,expounds the main method and its existing problems,and introducedsome classical linear and nonlinearmanifold learning algorithms,and analyses itsprinciple and the core thought, then gives the flow the person face recognitionalgorithm.(2)This paper introduces the basic knowledge of Gabor filtering and give aalgorithm about extracting feature of Gabor in face recognition,based on the analysisof the two dimensional Gabor filter performance and parameters selection,a methodwas proposed to speed extract the features of Gabor by FFT.(3)This paper gives an uncorrelated discriminant adaptive local tangent spacealignment algorithm(UDALLTSA). It analyzes the characteristics of Gabor filter andlinearlocal tangent space alignment algorithm,for unsupervised learning,base vectorconstraints and k-nearest neighbor selection and other defects of LLTSA, Throughexperiments that the performance of the algorithm is higher than the originalalgorithm,the robustness is good.(4)This paper gives the maximum scatter matrix is not related to the adaptivelocal linear method (UAFSLLE).It analyzes the characteristics of Gabor filter andthe linear locally linear embedding algorithm, It was improved by three aspects fromthe selection of adaptive neighborhood, introducing supervision information,Through experiments that the performance of the algorithm is higher than theoriginal algorithm,the robustness is very good.
Keywords/Search Tags:Face recognition, Manifold learning, Gabor filter, k-nearest neighbor, Base vector constraint
PDF Full Text Request
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